![]() For example, if the installed version in your system is python. * Running on (Press CTRL+C to quit) Contributingįor guidance on setting up a development environment and how to make aĬontribution to Flask, see the contributing guidelines. In a Python IDE, just copy and paste in the following code and run it (the version will come up in the output area): import sys print (sys. Make sure to install the referenced version of python along with your existing system python. MESAPC has been developed in a Python 3.7 environment using the following packages: f90nml 1.1.2 numpy 1.18.2 tqdm 4.45.0 Older versions of these modules have not been tested. To have this working properly, we strongly recommend working with a virtual environment. For unreleased (in development) documentation, see In Development Versions. route ( "/" ) def hello (): return "Hello, World!" $ flask run MESAPC makes use of of mulitple Python Libraries. Use the list below to select a version to view. Install and update using pip: $ pip install -U Flask A Simple Example # save this as app.py from flask import Flask app = Flask ( _name_ ). Check Python version This simple command works on all operating systems, including Windows, Linux, and MacOS. The current model is run with the training data set and produces a result, which is then compared with the target, for each input vector in the training data set. There are many extensions provided by theĬommunity that make adding new functionality easy. ![]() It is up to the developer to choose the tools and It began as a simple wrapper around WerkzeugĪnd Jinja and has become one of the most popular Python webįlask offers suggestions, but doesn’t enforce any dependencies or ![]() To make getting started quick and easy, with the ability to scale up toĬomplex applications. pyspark -version spark-submit -version spark-shell -version spark-sql -version. ![]() Flask is a lightweight WSGI web application framework. Like any other tools or language, you can use version option with spark-submit, spark-shell, pyspark and spark-sql commands to find the PySpark version.
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